自聚焦光纤中传导模的场分布

从亥姆霍兹方程出发，导出了自聚焦光纤中传导模在圆柱坐标系中的场分布形式，并给出了几个低阶模的分布图。     

Progressive Transformation of a Flux Rope to an ICME

The solar wind conditions at one astronomical unit (AU) can be strongly disturbed by interplanetary coronal mass ejections (ICMEs). A subset, called magnetic clouds (MCs), is formed by twisted flux ropes that transport an important amount of magnetic flux and helicity, which is released in CMEs. At 1 AU from the Sun, the magnetic structure of MCs is generally modeled by neglecting their expansion during the spacecraft crossing. However, in some cases, MCs present a significant expansion. We present here an analysis of the huge and significantly expanding MC observed by the Wind spacecraft during 9 – 10 November 2004. This MC was embedded in an ICME. After determining an approximate orientation for the flux rope using the minimum variance method, we obtain a precise orientation of the cloud axis by relating its front and rear magnetic discontinuities using a direct method. This method takes into account the conservation of the azimuthal magnetic flux between the inbound and outbound branches and is valid for a finite impact parameter (i.e., not necessarily a small distance between the spacecraft trajectory and the cloud axis). The MC is also studied using dynamic models with isotropic expansion. We have found (6.2±1.5)×10²⁰ Mx for the axial flux and (78±18)×10²⁰ Mx for the azimuthal flux. Moreover, using the direct method, we find that the ICME is formed by a flux rope (MC) followed by an extended coherent magnetic region. These observations are interpreted by considering the existence of a previously larger flux rope, which partially reconnected with its environment in the front. We estimate that the reconnection process started close to the Sun. These findings imply that the ejected flux rope is progressively peeled by reconnection and transformed to the observed ICME (with a remnant flux rope in the front part).     

Total Water Storage in Small Islands Using Multi-satellite Products: The case of Cyprus

The world’s longest international undersea water pipeline has recently been laid from southern Turkey to Northern Cyprus to address the water scarcity problems in the Cyprus Island. When completed, the project will add 19.8 million gallons of water annually for drinking and irrigation. Moreover, it will spur further development in the Turkish area divided from Greek community for four decades. Under such circumstances, satellite remote sensing provides a unique tool to evaluate the water policy for the entire island. The objective of this study is, therefore, to examine the potential of satellite-based remote sensing hydrologic models covering a small-scale Mediterranean island, which is under drought conditions. Satellite-based measurements such as GRACE (total water storage), TRMM (precipitation) and MODIS (evapotranspiration) data over a 1°–1° grid together with related information from global hydrological model, specifically WGHM and GLDAS, were collected for this purpose.     

A Hybrid Multi-scale Spatial Filtering and Minimum Spanning Forest for Spectral–Spatial Hyperspectral Image Classification

Integration of spatial and spectral information is an effective way in improving classification accuracy. In this article a new framework, based on multi-scale spatial weighted mean filtering (MSWMF) and minimum spanning forest, is proposed for the spectral–spatial classification of hyperspectral images. In the proposed framework, at first the image is smoothed by MSWMF and then the first eight principal components are extracted. Using support vector machine, at each scale of MSWMF, a classification map is produced in order to generate a marker map in the next step. Then, the minimum spanning forest is built on the marker map. Finally, in order to create a final classification map, all the classification maps of each scale are merged with a majority vote rule. The experimental results of the hyper-spectral images indicate that the suggested framework enhances the classification accuracy, in comparison with previously classification techniques. So, it is interesting for hyperspectral images classification.     

What governs the presence of residual vegetation in boreal wildfires?

Wildfires are frequent boreal forest disturbances in Canada, and emulating their patterns with forest harvesting has emerged as a common forest management goal. Wildfires contain many patches of residual vegetation of various size, shape, and composition; understanding their characteristics provides insights for improved emulation criteria. We studied the occurrence of residual vegetation within eleven boreal wildfire events in a natural setting; fires ignited by lightning, no suppression efforts, and no prior anthropogenic disturbances. Relative importance of the measurable geo-environmental factors and their marginal effects on residual presence are studied using Random Forests. These factors included distance from natural firebreaks (wetland, bedrock and non-vegetated areas, and water), land cover, and topographic variables (elevation, slope, and ruggedness index). We present results at spatial resolutions ranging from four to 64 m while emphasizing four and 32 m since they mimic IKONOS- and Landsat-type images. Natural firebreak features, especially the proximity to wetlands, are among the most important variables that explain the likelihood residual occurrence. The majority of residual vegetation areas are concentrated within 100 m of wetlands. Topographic variables, typically important in rugged terrain, are less important in explaining the presence of residuals within our study fires.     

Estimation of Partial Pressure of Carbon Dioxide and Air-Sea Fluxes in Hooghly Estuary Based on In Situ and Satellite Observations

An empirical model is developed and used with remotely sensed predictors: sea surface temperature (SST) and chlorophyll-a concentration (Chl-a), to compute surface water partial pressure of carbon dioxide (pCO_2w) and air-sea fluxes of CO₂ in the Hooghly estuary and its adjacent coastal oceans. In situ observations used here were based on measurements carried out in this region during winter and summer periods in 2008. The estimated pCO_2w compares well with the in situ observations at root mean square error ±18 μatm. In winter, estimated pCO_2w ranges between 320 and 500 μatm with large values (>400 μatm) on the south-western and south-eastern flanks of the coastal domain and lower values (340–375 μatm) on the main-channel. In summer, it remained spatially uniform at 450 μatm. Extrapolation of the results over the study region based on the Moderate Imaging Specroradiometer (MODIS) measured SST and Chl-a suggests that the region is a strong source of atmospheric CO₂ during the summer with net release of 0.095 Tg C year^?1 (equivalent to mean flux of 90 molC m^?2 year^?1) and is a weak source during the winter with net release of 0.006 Tg C yr^?1 (0.5 molC m^?2 year^?1) from the geographical extent of 6000 Km² area.     

基于车载激光点云的高精地图矢量化成图

针对车载激光点云中对各特征物提取结果后矢量化成图时的自动化问题,本文基于双方向积分法实现了边缘检测及矢量化成图,旨在保证特征物基本特征的同时,也保证点云的绝对精度。将输入的特征点云进行离群点过滤,以保证外包框算法特征点云的准确度;将三维点云按照外包框算法投影至最优平面,为后续沿各方向积分提供输入;利用八邻域KD-tree算法求出样本特征点云的均值邻域半径,依据邻域半径对各方向积分提供积分域中的微分元;根据提供的微分元沿各方向进行积分,在该积分元内找到距平面最值的最优解;按照积分结果构建点云索引,并根据点云特征构建模型,最终得到高精地图的矢量化点云。试验证明了该方法在处理实际问题时的可行性。     

改进粒子滤波器的室内地磁匹配精度研究

针对粒子滤波算法在室内地磁分布的连续性变化中会发生滤波发散,加之算法中重采样步骤使该现象恶化,直接导致室内定位过程中目标丢失的问题。该文受Hausdorff距离度量法中点集匹配思想的启发,提出了一种利用初定位误差作为最大粒子匹配距离的约束思想,通过缩小匹配空间的区域范围的方法来解决传统算法的发散问题。最后实验表明,此方法解决了粒子滤波器在地磁匹配中出现的滤波发散现象,同时使得定位结果更加快速收敛。